This invention relates to a tracking apparatus and method for tracking an object such as an aircraft and, in particular, to improvement thereof.
A tracking apparatus (or a tracking filter) is coupled with a detecting or sensing device such as a radar set. The detecting device periodically or successively detects a position of an object and produces a radar data set representative of position information of the object. The tracking apparatus calculates (or presumes) more correct tracking data representing the position (i.e. X and Y coordinates), velocity (i.e. a speed and an azimuth or a bearing angle) and so on of the object on the basis of the position information supplied from the detecting device.
As a conventional tracking apparatus, an xcex1-xcex2 system is well known. The xcex1-xcex2 system has tracking precision which is comparatively high when the object linearly moves at a uniform speed. However, the xcex1-xcex2 system has a problem that the tracking precision remarkably deteriorates when the object changes its traveling direction quickly (or when a sharp turn is made by the object).
To solve the problem, a proposal has been made about another system having high tracking precision even if the object changes its traveling direction quickly. The proposed tracking system receives the radar data sets successively supplied from the radar set. Each of the radar data set represents a position (or X-Y coordinates) of the object on a predetermined X-Y coordinate system and the detecting time at which the position is detected by the radar set. The tracking system finds first and second regression functions which are individually corresponding to time variations of the X coordinate and the Y coordinate on the predetermined X-Y coordinate system by the use of a plurality of the radar data sets. The first and the second regression functions comprise quadratic functions of time. By the use of the first regression function, the tracking system further finds a presumed X coordinate and its changing rate at the latest detecting time of the detected data sets. The changing rate of the presumed X coordinate is equal to an inclination of a first regression curve of the first regression function at the latest detecting time and corresponds to a speed of the object along a direction of an X axis of the predetermined X-Y coordinate system. Similarly, the tracking system finds a presumed Y coordinate and its changing rate at the latest detecting time by the use of the second regression function. The changing rate of the presumed Y coordinate is equal to an inclination of a second regression curve of the second regression function at the latest detecting time and corresponds to a speed of the object along a direction of a Y axis of the predetermined X-Y coordinate system.
Additionally, such tracking system is called hereinafter a regression curve adapting system.
The existing regression curve adapting system can more precisely presume the position of the object in comparison with the conventional xcex1-xcex2 system. However, the existing regression curve adapting system has a problem that the velocity presuming precision is lower than that of the xcex1-xcex2 system when the object changes its traveling direction quickly.
It is therefore an object of this invention to provide a tracking apparatus which can precisely find coordinates and velocity of an object.
Other object of this invention will become clear as the description proceeds.
According to the aspect of this invention, a tracking apparatus is for tracking an object by the use of a plurality of detecting data sets. The detecting data sets are successively supplied from a detecting device. The tracking apparatus finds a presumed position and a presumed velocity of the object at the latest detecting time of the detecting data sets to track the object. The tracking apparatus comprises a regression curve calculating portion to find two regression functions individually corresponding to time variation of X and Y coordinates of the object on a predetermined X-Y coordinate system by the use of the detected data sets. A position presuming portion is connected to the regression curve calculating portion and finds the presumed position by the use of the regression functions and the latest detecting time. A velocity presuming portion is connected to the regression curve calculating portion and finds the presumed velocity by the use of the regression functions and at least one of the other detecting times of the detected data sets.
According to another aspect of this invention, a tracking method is for tracking an object by the use of a plurality of detecting data sets. The detecting data sets are successively supplied from a detecting device and finds a presumed position and a presumed velocity of the object at the latest detecting time of the detecting data sets. The tracking method comprises the steps of finding two regression functions individually corresponding to time variation of X and Y coordinates of the object on a predetermined X-Y coordinate system by the use of said detected data sets, finding the presumed position by the use of the regression functions and the latest detecting time, and finding the presumed velocity by the use of the regression functions and at least one of the other detecting times of the detected data sets.